In multicarrier wireless transmission, a difference in the carrier frequency between a transmitter and a receiver causes overlapping of different subcarriers and, as such, interference, and performance degradation. In systems such as Orthogonal Frequency Division Multiplexing (OFDM), this may result in a loss of orthogonality between subcarriers. It is thus necessary to precisely estimate at the receiver the carrier frequency offset and correct it in the receiver itself (or via feedback at the transmitter). The correction can be made acting directly on the control signal of a voltage-controlled oscillator (VCO) or alternatively by signal processing. Frequency offset correction is usually followed by a phase tracking process, to compensate residual constellation rotation. Frequency offset estimation may be data-aided (e.g., based on a training sequence or on pilot tones) or non data-aided (e.g., based on the statistical properties of the data signal).
Conventional frequency offset estimation algorithms that achieve the foregoing are often based on the phase of the auto-correlation of the received signal. Such algorithms require a time periodicity in the signal. In practice, the periodicity may be designed in the training sequence, or the periodicity may be naturally present between cyclic prefix (CP) and the data portion of an OFDM signal. The phase of the auto-correlation is linearly proportional to the offset, and the maximum offset estimation range is inversely proportional to the time period of the received signal. This limits the maximum estimation range for algorithms based on the CP to half the inter-carrier spacing.
For a number of reasons, it is preferable to use a training sequence rather than CP. For example, the precision of frequency offset estimation depends on the number of samples used to compute the auto-correlation. With a single CP the number of samples does not guarantee a good estimation performance for a low signal-to-noise ratio (SNR), especially if the number of subcarriers is less than 100. So if the CP is used, it is necessary to take an average over several CPs. In packet-based systems, however, there is typically little time available for synchronization processing; thus, an a-priori known training sequence proves to be more efficient and better performing. Another reason why it is preferable to use a training sequence rather than CP, particularly germane in systems with a carrier frequency of several GHz and relatively narrow inter-carrier spacing, the use of commercial oscillators with a long-term accuracy of around 20 parts per million (PPM) results in a maximum offset that is well above the half inter-carrier spacing. It is thus necessary to make available a signal with a time period shorter than the distance from the CP to the tail of a data block.
In a packet-based, broadband multi-carrier system, where a training sequence is adopted, several frequency offset estimation algorithms have been developed, but, in systems wherein the training sequence should be as short as possible, no such systems allow a wide offset estimation range to be combined with high estimation accuracy. Moreover, no such systems guarantee high estimation accuracy for low SNR or SIR, especially in multipath fading channel condition. Finally, it should be noted that in such systems, the estimation of a frequency offset performed with a MIMO antenna system has been utilized to improve the robustness against multipath fading, but has not been fully utilized yet to improve offset estimation accuracy.
Accordingly, a continuing search has been directed to the development of an approach which improves frequency offset estimation accuracy without reducing the estimation range. Such frequency offset estimation would preferably be performed using algorithms which (1) are of limited computational complexity to allow for fast processing, (2) feature a detection range able to cover all practical frequency offsets, (3) maintain a given accuracy even at the lower edge of the operating SNR region, and (4), if based on a training sequence, then the same sequence has to be bandwidth-efficient and with a low Peak-to-Average Power Ratio (PAPR).